Whisper Large V2 - Mongolian LoRA
This model is a fine-tuned version of openai/whisper-large-v2 on the nrlt/dataset-mn-preprocessed dataset. It achieves the following results on the evaluation set:
- Loss: 0.3712
- Wer: 38.7426
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4376 | 1.4151 | 500 | 0.6133 | 65.9333 |
| 0.4635 | 2.8302 | 1000 | 0.4080 | 49.1834 |
| 0.3072 | 4.2453 | 1500 | 0.3462 | 44.3583 |
| 0.228 | 5.6604 | 2000 | 0.3182 | 40.4206 |
| 0.1724 | 7.0755 | 2500 | 0.3149 | 38.7426 |
| 0.1246 | 8.4906 | 3000 | 0.3212 | 39.0260 |
| 0.0963 | 9.9057 | 3500 | 0.3326 | 42.9935 |
| 0.0679 | 11.3208 | 4000 | 0.3589 | 39.4287 |
| 0.0512 | 12.7358 | 4500 | 0.3712 | 38.7426 |
Framework versions
- PEFT 0.19.1
- Transformers 4.46.3
- Pytorch 2.4.1+cu124
- Datasets 2.18.0
- Tokenizers 0.20.3